News & Events

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.

User menu

You are here

Markov Chain Monte Carlo and Langevin equations on a Stratification

Tuesday, May 9, 2023 - 11:00 to 12:00
Miranda Holmes-Cerfon, Associate Professor, UBC Mathematics
Statistics Seminar
ESB 4192 / Zoom

To Join via Zoom: To join this seminar virtually, please request Zoom connection details from headsec [at]

Title: Markov Chain Monte Carlo and Langevin equations on a Stratification

Abstract: Many sampling problems involve constraints — statistical models may involve relationships between parameters; noisy physical systems may involve stiff forces that constrain the system near a manifold, such as stiff bonds between particles. In some cases the constraints are not fixed, but rather can be added or removed (such as when bonds between particles form or break), so the probability measure of interest lives on sets of different dimensions. How can we sample from such a measure? I will introduce an MCMC algorithm to sample a probability measure supported on a stratification: a union of manifolds of different dimensions, glued together at their boundaries in a nice enough way. I will show this can accelerate simulations of interacting particles by up to several orders of magnitude. Then I will talk about our progress toward simulating Langevin equations on a stratification, which harnesses the theory of sticky diffusions. These algorithms are motivated by applications to systems of interacting particles, and I will be interested to learn about other areas of application.